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M. Nanni, Raffaetà, A., Renso, C., and Turini, F., “Deductive and Inductive Reasoning on Trajectories”, in SEBD, 2004, pp. 98-105.
M. Nanni, Raffaetà, A., Renso, C., and Turini, F., “Deductive and Inductive Reasoning on Spatio-Temporal Data”, in INAP/WLP, 2004, pp. 98-115.
M. Nanni and Pedreschi, D., “Time-focused clustering of trajectories of moving objects”, J. Intell. Inf. Syst., vol. 27, pp. 267-289, 2006.
M. Nanni, Raffaetà, A., Renso, C., and Turini, F., “\newblock{A Declarative Framework for Reasoning on Spatio-temporal Data}”, 2004.
M. Nanni, Kuijpers, B., Körner, C., May, M., and Pedreschi, D., “Spatiotemporal Data Mining”, in Mobility, Data Mining and Privacy, 2008, pp. 267-296.
M. Nanni, Trasarti, R., Renso, C., Giannotti, F., and Pedreschi, D., “Advanced knowledge discovery on movement data with the GeoPKDD system”, in EDBT, 2010, pp. 693-696.
M. Nanni, Trasarti, R., Renso, C., Giannotti, F., and Pedreschi, D., “Advanced knowledge discovery on movement data with the GeoPKDD system”, in EDBT, 2010, pp. 693-696.
M. Nanni and Trasarti, R., “Querying and mining trajectories with gaps: a multi-path reconstruction approach (Extended Abstract)”, in SEBD, 2010, pp. 126-133.
M. Nanni and Trasarti, R., “K-BestMatch Reconstruction and Comparison of Trajectory Data”, in ICDM Workshops, 2009, pp. 610-615.
M. Nanni and Trasarti, R., “K-BestMatch Reconstruction and Comparison of Trajectory Data”, in ICDM Workshops, 2009, pp. 610-615.
M. Nanni, Trasarti, R., Cintia, P., Furletti, B., Renso, C., Gabrielli, L., Rinzivillo, S., and Giannotti, F., “Mobility Profiling”, in Data Science and Simulation in Transportation Research, IGI Global, 2014, pp. 1-29.
M. Nanni, Trasarti, R., Furletti, B., Gabrielli, L., Van Der Mede, P., De Bruijn, J., de Romph, E., and Bruil, G., “Transportation Planning Based on {GSM} Traces: {A} Case Study on Ivory Coast”, in Citizen in Sensor Networks - Second International Workshop, CitiSens 2013, Barcelona, Spain, September 19, 2013, Revised Selected Papers, 2013.
M. Nanni, Trasarti, R., Furletti, B., Gabrielli, L., Van Der Mede, P., De Bruijn, J., de Romph, E., and Bruil, G., “MP4-A Project: Mobility Planning For Africa”, in In D4D Challenge @ 3rd Conf. on the Analysis of Mobile Phone datasets (NetMob 2013), Cambridge, USA, 2013.
M. Nanni, Trasarti, R., Monreale, A., Grossi, V., and Pedreschi, D., “Driving Profiles Computation and Monitoring for Car Insurance CRM”, Journal ACM Transactions on Intelligent Systems and Technology (TIST), vol. 8, pp. 14:1–14:26, 2016.
M. Nanni, Nijssen, S., O'Sullivan, B., Paparrizou, A., Pedreschi, D., and Simonis, H., “The Inductive Constraint Programming Loop”, Data Mining and Constraint Programming: Foundations of a Cross-Disciplinary Approach, vol. 10101, p. 303, 2017.
M. Nanni, Kotthoff, L., Guidotti, R., O'Sullivan, B., and Pedreschi, D., “ICON Loop Carpooling Show Case”, Data Mining and Constraint Programming: Foundations of a Cross-Disciplinary Approach, vol. 10101, p. 310, 2017.
M. Nanni, Raffaetà, A., Renso, C., and Turini, F., “Spatio-Temporal Data”, Spatio-Temporal Databases: Flexible Querying and Reasoning, p. 75, 2013.
M. Nanni, Trasarti, R., and Giannotti, F., “Movement Behaviour Recognition for Water Activities”, in Personal Analytics and Privacy. An Individual and Collective Perspective - First International Workshop, {PAP} 2017, Held in Conjunction with {ECML} {PKDD} 2017, Skopje, Macedonia, September 18, 2017, Revised Selected Papers, 2017.
M. Nanni, Andrienko, G., Barabasi, A. - L., Boldrini, C., Bonchi, F., Cattuto, C., Chiaromonte, F., Comandé, G., Conti, M., Coté, M., Dignum, F., Dignum, V., Domingo-Ferrer, J., Ferragina, P., Giannotti, F., Guidotti, R., Helbing, D., Kaski, K., Kertész, J., Lehmann, S., Lepri, B., Lukowicz, P., Matwin, S., Jiménez, D. Megías, Monreale, A., Morik, K., Oliver, N., Passarella, A., Passerini, A., Pedreschi, D., Pentland, A., Pianesi, F., Pratesi, F., Rinzivillo, S., Ruggieri, S., Siebes, A., Torra, V., Trasarti, R., van den Hoven, J., and Vespignani, A., “Give more data, awareness and control to individual citizens, and they will help COVID-19 containment”, 2021.